Contact centers, such as Automatic Call Distribution or ACD systems, are employed by many enterprises to service customer contacts. A typical contact center includes a switch and/or server to receive and route incoming packet-switched and/or circuit-switched contacts and one or more resources, such as human agents and automated resources (e.g., Interactive Voice Response (IVR) units), to service the incoming contacts. Contact centers distribute contacts, whether inbound or outbound, for servicing to any suitable resource according to predefined criteria. In many existing systems, the criteria for servicing the contact from the moment that the contact center becomes aware of the contact until the contact is connected to an agent are customer-specifiable (i.e., programmable by the operator of the contact center), via a capability called vectoring. Normally in present-day ACDs when the ACD system's controller detects that an agent has become available to handle a contact, the controller identifies all predefined contact-handling skills of the agent (usually in some order of priority) and delivers to the agent the highest-priority oldest contact that matches the agent's highest-priority skill. Agents with a higher skill are normally preferred over agents with lower skill levels when assigning an agent to a contact. When agents have multiple skills, the controller is more likely to select a contact for which the agent has a high skill level over a contact for which the agent has a lesser skill level. Generally, the only condition that results in a contact not being delivered to an available agent is that there are no contacts waiting to be handled.
Contact-distribution algorithms ultimately seek to maximize contact center performance and profitability. That may involve minimizing cost, maximizing contact throughput, and/or maximizing revenue, among others. Skills-based routing, which allows each agent to be slotted into a number of agent groups based on the agent's skill types and levels, is an attempt to maximize contact center performance and profitability. Skills-based routing systems have been further modified by introducing, as criterion in assigning work items to available agents, the service level associated with each work item. Service level refers to the proportion of work item transactions meeting specified objectives or goals. Service level is typically measured over some period of time or over some number of transactions. Examples of service levels are the percentage of customer problems resolved without further activity (one-and-done), the proportion of telephone calls handled by a qualified representative without requiring a transfer or referral to another agent, the proportion of telephone calls that can be connected to a server without delay, the proportion of email requests that are answered within 24 hours, the proportion of transactions handled not resulting in a customer complaint, the proportion of preferred customer calls handled by fully qualified agents, the percentage of Spanish customers handled by an agent fluent in Spanish, the percentage of telephone calls not abandoned by the customer before connection to an agent, the percentage of customer inquiry telephone calls that are not blocked at the central office switch, the percentage of customer sessions with the self-service World Wide Web pages that are not aborted while waiting for a display, the percentage of customer requests via telephone that can be completed immediately while on the phone, and the percentage of priority telephone calls answered within 8 seconds and handled properly by a qualified server, to name but a few.
A contact center's goal for a service level is a particular desired value of the service level. The goal is said to be satisfied or attained if the attained or measured service level is at least as high as the desired service level for the goal. Conversely, the goal is said to be not satisfied or unattained if the realized service level is less than the desired service level. For example, the goal of at least 85% of telephone calls from preferred customers each day being answered within 12 seconds would be attained if, among the telephone calls from preferred customers during the current day, 87% were answered within 12 seconds; inversely, if only 84% of such calls are answered within 12 seconds, the goal would be unattained.
In existing skills-based contact routing algorithms using service levels as part of the work item routing determination, the skill level is normally a simple integer assigned to each skill that the agent can perform and is a composite of all of the various and numerous aspects of agent proficiency or expertise. One example of such a contact routing algorithm is described in U.S. Pat. No. 6,173,053 (“the '053 patent”). The algorithm described in the '053 patent uses agent profiles to identify a best agent to service an incoming contact. Each agent has a service profile for each contact type or skill that they handle. As will be appreciated, a “contact type” is determined by segmentation using suitable criteria, such as language, intent, geography, channel, and the like. A service profile includes present values of a number of service metrics, such as agent proficiency, profitability, customer satisfaction, and agent satisfaction. When a contact of a particular type is available for servicing, the present values of the service metrics of the service profile of each agent who is available to handle the contact are combined into a score according to one of a number of formulas, which correspond to that contact type, and the agent with the best score is assigned to the contact. When the assigned agent finishes handling the contact, his or her performance is evaluated based on the service metrics, and the valuations are used to revise the present values of the service metrics of that agent's service profile. The revision process gives more weight to valuations of more-recently-handled contacts to reflect both long-term and short-term agent performance trends and variations.
These contact allocation algorithms can have drawbacks. By focusing solely on a composite score they ignore other aspects of agent proficiency. Such aspects include agent effectiveness, speed, efficiency, experience, cross-sell ability, and the like. They also fail to consider the interplay between contact center goals and aspects of agent proficiency. When different sets of goals are unmet in the contact center, it may advantageous to focus on different aspects of agent proficiency to address the unmet goal sets. By way of illustration, when there is limited work and a surplus of available agents the optimal strategy may be to focus on the agent aspect of effectiveness and assign what work there is to the most effective agents. When work queues are excessively long, the optimal strategy may be to focus on the agent aspect of speed and assign work to the fastest agents.